Text and spatial data mining

Parcellation of the human brain Parcellation of the human brain by combining text mining and spatial data mining within a neuroinformatics database. Text mining: Analysis of scientific abstracts. Spatial data mining: Modeling of the distribution of Talairach coordinates. Seek communality between the the text representation and spatial representation by multivariate analysis

Visualizing data mining results with the Brede tools

A few neuroinformatics databases now exist that record results from neuroimaging studies in the form of brain coordinates in stereotaxic space. The Brede Toolbox was originally developed to extract, analyze and visualize data from one of them --- the BrainMap database. Since then the Brede Toolbox has expanded and now includes its own database with coordinates along with ontologies for brain regions and functions: The Brede Database. With Brede Toolbox and Database combined we setup automated workflows for extraction of data, mass meta-analytic data mining and visualizations. Most of the Web presence of the Brede Database is established by a single script executing a workflow involving these steps together with a final generation of Web pages with embedded visualizations and links to interactive three-dimensional models in the Virtual Reality Modeling Language. Apart from the Brede tools I briefly review alternate visualization tools and methods for Internet-based visualization and information visualization as well as portals for visualization tools

Early and Late Stage Mechanisms for Vocalization Processing in the Human Auditory System

The human auditory system is able to rapidly process incoming acoustic information, actively filtering, categorizing, or suppressing different elements of the incoming acoustic stream. Vocalizations produced by other humans (conspecifics) likely represent the most ethologically-relevant sounds encountered by hearing individuals. Subtle acoustic characteristics of these vocalizations aid in determining the identity, emotional state, health, intent, etc. of the producer. The ability to assess vocalizations is likely subserved by a specialized network of structures and functional connections that are optimized for this stimulus class. Early elements of this network would show sensitivity to the most basic acoustic features of these sounds; later elements may show categorically-selective response patterns that represent high-level semantic organization of different classes of vocalizations. A combination of functional magnetic resonance imaging and electrophysiological studies were performed to investigate and describe some of the earlier and later stage mechanisms of conspecific vocalization processing in human auditory cortices. Using fMRI, cortical representations of harmonic signal content were found along the middle superior temporal gyri between primary auditory cortices along Heschl\u27s gyri and the superior temporal sulci, higher-order auditory regions. Additionally, electrophysiological findings also demonstrated a parametric response profile to harmonic signal content. Utilizing a novel class of vocalizations, human-mimicked versions of animal vocalizations, we demonstrated the presence of a left-lateralized cortical vocalization processing hierarchy to conspecific vocalizations, contrary to previous findings describing similar bilateral networks. This hierarchy originated near primary auditory cortices and was further supported by auditory evoked potential data that suggests differential temporal processing dynamics of conspecific human vocalizations versus those produced by other species. Taken together, these results suggest that there are auditory cortical networks that are highly optimized for processing utterances produced by the human vocal tract. Understanding the function and structure of these networks will be critical for advancing the development of novel communicative therapies and the design of future assistive hearing devices

Cognitive, Neural, and Educational Contributions to Mathematics Performance: A Closer Look at the Roles of Numerical and Spatial Skills

The principal aims of this thesis were to (1) provide new insights into the cognitive and neural associations between spatial and mathematical abilities, and (2) translate and apply findings from the field of numerical cognition to the teaching and learning of early mathematics. Study 1 investigated the structure and interrelations amongst cognitive constructs related to numerical, spatial, and executive function (EF) skills and mathematics achievement in 4- to 11-year old children (N=316). Results revealed evidence of highly related, yet separable, cognitive constructs. Together, numerical, spatial, and EF skills explained 84% of the variance in mathematics achievement (controlling for chronological age). Only numerical and spatial skills, but not EF, were unique predictors of mathematics performance. Spatial visualization was an especially strong predictor of mathematics. Study 2 examined where and under what conditions spatial and numerical skills converge and diverge in the brain. An fMRI meta-analysis was performed to identify brain regions associated with basic symbolic number processing, mental arithmetic, and mental rotation. All three cognitive processes were associated with activity in and around the bilateral intraparietal sulcus (IPS). There was also evidence of overlap between symbolic number and arithmetic in the left IPS and overlap between mental rotation and arithmetic in the middle frontal gyri. Together, these findings provide a process-based account of common and unique relations between spatial and numerical cognition. Study 3 addressed the research-to-practice gap in the areas of numerical cognition research and mathematics education. A 25-hour Professional Development (PD) model for teachers of Kindergarten–3rd Grade was designed, implemented, and tested. Results indicated that the PD was effective at increasing teachers’ self-perceived numerical cognition knowledge and students’ general numeracy skills. However, there were notable differences in the effects of the PD across the two sites studied, with much stronger effects at one site than the other. Thus, critical questions remain as to when and why the model may be effective in some school contexts but not others. Together, these studies contribute to an improved understanding of the underlying relations amongst spatial, numerical, and mathematical skills and a viable new approach to better integrate research and practice

Reproducibility of BOLD-based functional MRI obtained at 4

Abstract: The reproducibility of activation patterns in the whole brain obtained by functional magnetic resonance imaging (fMRI) experiments at 4 Tesla was studied with a simple finger-opposition task. Six subjects performed three runs in one session, and each run was analyzed separately with the t-test as a univariate method and Fisher's linear discriminant analysis as a multivariate method. Detrending with a first-and third-order polynomial as well as logarithmic transformation as preprocessing steps for the t-test were tested for their impact on reproducibility. Reproducibility across the whole brain was studied by using scatter plots of statistical values and calculating the correlation coefficient between pairs of activation maps. In order to compare reproducibility of ''activated'' voxels across runs, subjects and models, 2% of all voxels in the brain with the highest statistical values were classified as activated. The analysis of reproducible activated voxels was performed for the whole brain and within regions of interest. We found considerable variability in reproducibility across subjects, regions of interest, and analysis methods. The t-test on the linear detrended data yielded better reproducibility than Fisher's linear discriminant analysis, and therefore seems to be a robust although conservative method. Preliminary data indicate that these modeling results may be reversed by preprocessing to reduce respiratory and cardiac physiological noise effects. The reproducibility of both the position and number of activated voxels in the sensorimotor cortex was highest, while that of the supplementary motor area was much lower, with reproducibility of the cerebellum falling in between the other two areas

Neuroinformatics in Functional Neuroimaging

This Ph.D. thesis proposes methods for information retrieval in functional neuroimaging through automatic computerized authority identification, and searching and cleaning in a neuroscience database. Authorities are found through cocitation analysis of the citation pattern among scientific articles. Based on data from a single scientific journal it is shown that multivariate analyses are able to determine group structure that is interpretable as particular “known ” subgroups in functional neuroimaging. Methods for text analysis are suggested that use a combination of content and links, in the form of the terms in scientific documents and scientific citations, respectively. These included context sensitive author ranking and automatic labeling of axes and groups in connection with multivariate analyses of link data. Talairach foci from the BrainMap ™ database are modeled with conditional probability density models useful for exploratory functional volumes modeling. A further application is shown with conditional outlier detection where abnormal entries in the BrainMap ™ database are spotted using kernel density modeling and the redundancy between anatomical labels and spatial Talairach coordinates. This represents a combination of simple term and spatial modeling. The specific outliers that were found in the BrainMap ™ database constituted among others: Entry errors, errors in the article and unusual terminology

From Photography to fMRI

Hysteria, a mysterious disease known since antiquity, is said to have ceased to exist. Challenging this commonly held view, this is the first cross-disciplinary study to examine the current functional neuroimaging research into hysteria and compare it to the nineteenth-century image-based research into the same disorder. Paula Muhr's central argument is that, both in the nineteenth-century and the current neurobiological research on hysteria, images have enabled researchers to generate new medical insights. Through detailed case studies, Muhr traces how different images, from photography to functional brain scans, have reshaped the historically situated medical understanding of this disorder that defies the mind-body dualism